• 전자통신동향분석
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• 제35권1호
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• pp.71-79
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• 2020

Since Amazon announced plans to deliver goods to customers using drones, many countries and companies have become interested in drone logistics delivery services and have begun testing drone delivery for various goods based on service scenarios. Whenever there is news of a successful drone delivery anywhere in the world, people increasingly expect the delivery of goods through drones. Although delivery services using drones are currently in a trial-and-error stage, given technical limitations and institutional and social constraints, a complete shift to drone logistics delivery is not yet possible. In anticipation of the drone logistics delivery service, recent drone delivery tests, current service trends, and requirements for drone delivery service will be examined.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2019년도 추계학술대회
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• pp.230-232
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• 2019

There is an accelerating need for ocean sensing where autonomous vehicles can play a key role in assisting engineers, researcher and scientists with environmental monitoring and collecting oceanographic data. This paper is performed to develops an autonomous sailing drone to be used as a sensor carrying platform for autonomous data acquisition at Sea. From a sailing drone design viewpoint, it is important to establish reliable prediction methods for sailing drone's resistance. The required power for the propulsion unit depends on the ship resistance and speed. There are three solutions for the prediction of ship resistance as follow analytical methods, model tests in tanks and Computational Fluid Dynamics (CFD). The present paper aims at simulating sailing drone friction resistance using numerical method. The dynamic mesh motion is used to describe the sailing drone movement.

• 로봇학회논문지
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• 제12권4호
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• pp.425-431
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• 2017

As drones gain more popularity these days, drone detection becomes more important part of the drone systems for safety, privacy, crime prevention and etc. However, existing drone detection systems are expensive and heavy so that they are only suitable for industrial or military purpose. This paper proposes a novel approach for training Convolutional Neural Networks to detect drones from images that can be used in embedded systems. Unlike previous works that consider the class probability of the image areas where the class object exists, the proposed approach takes account of all areas in the image for robust classification and object detection. Moreover, a novel loss function is proposed for the CNN to learn more effectively from limited amount of training data. The experimental results with various drone images show that the proposed approach performs efficiently in real drone detection scenarios.

• International Journal of Advanced Culture Technology
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• 제12권2호
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• pp.286-298
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• 2024

The rapid advancement of drone technology has significantly altered the landscape of modern warfare, presenting both opportunities and challenges for military forces worldwide. As drones become increasingly sophisticated, capable of performing complex missions such as reconnaissance, surveillance, and precision strikes, the development of effective air defense systems has become a critical priority. This study examines the current state of drone and air defense technologies, analyzing their impact on military strategies, tactics, and the future battlefield environment. By exploring the patterns of technological evolution, the limitations of existing air defense systems, and the potential consequences of drone proliferation, this research highlights the need for adaptive, innovative approaches to counter emerging threats. The findings underscore the importance of investing in advanced detection and interception capabilities, developing comprehensive counter-drone doctrines, and fostering international cooperation to address the ethical and legal challenges posed by the military use of drones. As the competition between drone and air defense technologies continues to intensify, policymakers and military leaders must proactively engage in shaping the future of warfare to ensure national security and stability in an increasingly complex world.

• 문화기술의 융합
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• 제9권2호
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• pp.327-332
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• 2023

2022년 12월 26일 북한의 드론 도발은 8년 만에 재개되었다. 이번 위협은 수도권은 물론 대통령실 경호를 위한 비행금지구역까지 해당되었으며, 이에 대한 우리 군의 대응이 적절하지 못해 큰 논란이 되고 있다. 이러한 가운데 국내에서는 소형드론의 비행 금지 및 제한구역의 불법 침입에 따른 문제점이 점증하고 있으며 해외에서는 테러 공격에 활용되는 등 그 위협이 실체화되고 있다. 본 고에서는 이러한 드론의 위협에 대해 '대드론(Counter-Drone)' 개념과 이와 관련된 기술을 고찰하고 국내 및 해외의 소형드론 위협 사례를 통해 함의를 도출, 대드론체계의 발전방향을 제시하였다. 북한의 드론위협은 더욱 다종화, 다량화, 고도화되어 보다 대담한 공격 및 도발로 이루어질 것으로 보인다. 따라서 우리 군은 통합관제체계 및 대드론체계의 조기 전력화, 소형드론의 위협에 대응한 합동 및 제병협동 차원의 대응, 한·미 대드론 연합작전 수행능력 등을 추진해 나아가야할 것이다.

• 한국멀티미디어학회논문지
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• 제20권6호
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• pp.927-934
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• 2017

As the technology of drone develops, the use of drone is increasing, In addition, the types of sensors that are inside of smart phones are becoming various and the accuracy is enhancing day by day. Various of researches are being progressed. Therefore, we need to control drone by using smart phone's sensors. In this paper, we propose the most suitable machine learning model that matches the gyro sensor data with drone's moving. First, we classified drone by it's moving of the gyro sensor value of 4 and 8 degree of freedom. After that, we made it to study machine learning. For the method of machine learning, we applied the One-Rule, Neural Network, Decision Tree, and Navie Bayesian. According to the result of experiment that we designated the value from gyro sensor as the attribute, we had the 97.3 percent of highest accuracy that came out from Naive Bayesian method using 2 attributes in 4 degree of freedom. On and the same, in 8 degree of freedom, Naive Bayesian method using 2 attributes showed the highest accuracy of 93.1 percent.

• 한국생산제조학회지
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• 제26권2호
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• pp.230-237
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• 2017

Various drones have extended application area very fast. In this paper, we define two contradictions in designing a portable-size drone by using TRIZ technique. The first is a physical contradiction between high rigidity and good portability, and the second is a technical contradiction between high stability and good portability. Through TRIZ technique, six design principles, which guide direction for optimal design, were driven. Consequently, an umbrella mechanism and design criteria were proposed for a portable-size drone. Detail design is verified through finite element method. Test results for the portable-size prototype drone show good performance, and prove its usefulness to be equivalent to a general full-size drone.

• 전기학회논문지
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• 제66권1호
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• pp.179-185
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• 2017

Communication technologies hold a significant place in the swarm flight of drones for surveillance, inspection of disasters and calamities, entertainment performances, and drone collaborations. A GCS(ground control station) for the control of drone swarms needs its devoted communication method to control a large number of drones at the same time. General drone controllers control drones by connecting transmitters and drones in 1:1. When such an old communication method is employed to control many drones simultaneously, problems can emerge with the control of many transmitter modules connected to a GCS and frequency interference among them. This study implemented a transmitter controller to control many drones simultaneously with a communication chip of 2.4GHz ISM band and a Cortex M4-based board. It also designed a GCS to control many transmitter controllers via a network. The hierarchical method made it possible to control many more drones. In addition, the problem with frequency interference was resolved by implementing a time- and frequency-sharing method, controlling many drones simultaneously, and adding the frequency hopping feature. If PPM and S.BUS protocol features are added to it, it will be compatible with more diverse transmitters and drones.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.163-169
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• 2021

In this paper, we implemented a deep learning-based automatic object tracking and handy motion control drone system and analyzed the performance of the proposed system. The drone system automatically detects and tracks targets by analyzing images obtained from the drone's camera using deep learning algorithms, consisting of the YOLO, the MobileNet, and the deepSORT. Such deep learning-based detection and tracking algorithms have both higher target detection accuracy and processing speed than the conventional color-based algorithm, the CAMShift. In addition, in order to facilitate the drone control by hand from the ground control station, we classified handy motions and generated flight control commands through motion recognition using the YOLO algorithm. It was confirmed that such a deep learning-based target tracking and drone handy motion control system stably track the target and can easily control the drone.

• 한국전자통신학회논문지
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• 제16권5호
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• pp.969-974
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• 2021

우리나라는 국토교통 7대 신산업 중 하나로 무인 항공기의 하나의 종류인 드론 산업을 선정하여 드론 산업활성화를 위해 드론특별자유화구역을 선정하고 드론 관련 법안을 신설, 개정하는 등의 노력을 하고 있다. 이러한 노력을 통해 향후 드론 택배, 드론 택시 등이 운용될 것으로 보인다. 이에 드론과 고정익, 회전익 등의 기존 항공기들과의 다자간 충돌 회피 시스템을 구축하여 발생 가능한 드론과 항공기간 공중 충돌에 대비하여야 한다. 이에. 그 방안을 제시하려 한다.